Adaptive laminate inspection

Project description

The SMR minor focuses on real world problems, composite problems in this case. The customer, TNO, has the following problem: Plate-like curved parts that fulfil critical functions during operation, such as the skin of an airplane, pipelines, and windows in fusion reactors, need to be thoroughly inspected before they can be put into service. Ultrasound inspection tools are typically used to non-destructively assess the quality of such parts. There is a trend from performing point measurements at the structure by hand to automated scanning of the entire structure. For advanced inspection, these tools needs to be aligned with the plate’s local normal direction with ever smaller tolerances.

In practice, besides orientation, these curved plates deviate slightly from their designed shape. Because of these deviations and combined with tight alignment requirements of the inspection tool, the available CAD data of the plate is insufficient to perform automated inspection. As a result, the inspection tool needs to be oriented adaptively during scanning. The local (deviated) surface normal needs to be determined and the orientation and position of the inspection tool needs to be adjusted while the tool moves over the plate.

The solution

With use of a Kawasaki robot a solution has been found. An adaptive scanning system has been set up to determine, store and refollow the local normal on every position to the plate. The system can calibrate itself and fully automatic scan, store, and process the local normal on a set interval.

Laser vs ultrasound

As described in the project description the plates used in production are inspected with ultrasound, due to the additional complications of ultrasound the first working prototype is carried out with laser. Since the working principles of laser and ultrasound are comparable the developed system should work in the real situation.

Angle detection

The angle which the robot has to rotate is calculated by using the known refraction index and the thickness of the material. The variables are put in a formula which is used by the algorithm. When the plate rotates relative to the laser, the spot on the CMOS camera sensor moves. By measuring the offset of the spot from the 0° position the angle-to-move is calculated.

User interface

Through the Graphical User Interface (GUI) the path length, maximum rotation and travel distance can be set to reach the accuracy that is needed in a typical situation. The plate thickness can be adjusted in the software.

Re-follow plate

While scanning, the positions of the local normal on the plate are stored in an Excel file. After the scan the system can load the Excel file and follow the scanned path. While the path is being followed pictures can be taken to check the position of the laser on the sensor.

The algorithm

The algorithm is set up to provide the most accurate results, in total the tolerances are within 1° (-0.5°/ +0.5°). To reach this level of precision the following steps are taken:

Calibration; the camera calibrates above the plate to handle minimum misalignment. The location of the spot above the plate is set as the reference position. At that moment the laser is perpendicular to the CMOS.

The robot moves the camera and laser down to scan the plate. Now there are two possible options:

The laser is visible: The distance of the spot to the calibrated centre is read out and translated in to the angle the robot has to turn.

The laser is not visible: The robot performs a global scan, i.e. the robot moves with small steps and rotates in positive and negative direction around the plate to find a spot on the sensor. Once the spot is found step 2.1 is performed.

The robot rotates the calculated angle.

The software checks the position to be within 1° related to the local normal of the plate. If not the robot moves the remaining angle.

The robot moves to the next position and goes on with step 2.

End of product, the robot reaches the end, moves up and waits till further orders.

Test results

In the picture above the angle of the plate related to the base frame of the robot is shown. The deviations in the graph are the results of the internal stresses in the plate. This causes an change to the refraction index.

In the picture above the robot coordinates are plotted against the moved distance. The result is a graph that shows the shape of the plate.

Conclusion

During the project the project group developed a working test setup. It is a proof of principle for automated plate inspection. Through this project the theory is proven. The project was successful and the requirements of the client were achieved. The system is capable of determining the local normal with the needed accuracy and follow this path. The client will continue the project to improve the system further. The client can invest in further research to inspect plates with ultrasound technology.